There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

The science and technology of ultracapacitors are reviewed for a number of electrode materials, including carbon, mixed metal oxides, and conducting polymers. More work has been done using microporous carbons than with the other materials and most of the commercially available devices use carbon electrodes and an organic electrolytes. The energy density of these devices is 3¯5 Wh/kg with a power density of 300¯500 W/kg for high efficiency (90¯95%) charge/discharges. Projections of future developments using carbon indicate that energy densities of 10 Wh/kg or higher are likely with power densities of 1¯2 kW/kg. A key problem in the fabrication of these advanced devices is the bonding of the thin electrodes to a current collector such the contact resistance is less than 0.1 cm2. Special attention is given in the paper to comparing the power density characteristics of ultracapacitors and batteries. The comparisons should be made at the same charge/discharge efficiency.

Ultracapacitors: Why, How, and Where is the Technology

http://ieeexplore.ieee.org/iel5/5610941/5624686/05624745.pdf

Power electronics

Light-Emitting Diodes. (Monographs in Electrical and Electronic Engineering.) By A. A. Bergh and P. J. Dean. Pp. viii+591. (Clarendon: Oxford; Oxford University: London, 1976.) £22.

/pdf/light-emitting-diodes-ubzde6g9qc.pdf

Light-emitting diodes

This paper proposes a reliability-oriented component sizing procedure for the cost benchmarking of capacitive DC-links. The sizing of devices for different solutions is based on consistent specifications and design margins (e.g., designed lifetime, maximum junction temperature, and maximum total harmonic distortion). A scalability analysis is also presented to identify the most cost-effective solution in different application scenarios.

A reliability-oriented component sizing procedure for cost benchmarking of capacitive DC-links

Film capacitors are used in power electronic converters due to their higher reliability compared to aluminum electrolytic capacitors. Humidity is one of the critical factors affecting the aging of film capacitors. However, the existing methodologies for the lifetime estimation of film capacitors rarely consider humidity. Besides, sometimes it is hard to obtain a large amount of data in the accelerated aging test of the device. To solve these problems, this article proposes a lifetime estimation methodology that requires fewer data and testing time. In the proposed methodology, humidity dummy variables are introduced into the degradation model based on the multivariate linear regression (MLR) algorithm. The impact of introduced dummy variables with different structures on the degradation model is studied and the effect of the proposed lifetime estimation method is verified. The results show that the proposed scheme achieves a comparable performance and can be valid in reality.

A Dummy-Variable Model for Humidity-Influenced DC Film Capacitors Lifetime Estimation

The capacitor sizing for the capacitive DC link of a single-phase inverter is usually based on a pre-determined voltage ripple limitation, ripple current capability, and/or energy storage requirement. Nevertheless, it is lack of justifications of the pre-determined criteria. This paper aims to investigate the dependency between the DC-link capacitance and the converter-level efficiency of a single-phase inverter. The major sources of the converter power loss, i.e., IGBTs, capacitors, and inductors, are quantitatively modeled considering the varying DC-link voltage. It provides an additional dimension to optimize the capacitor selection for capacitive DC links. The theoretical analyses are verified by both simulations and experiments.

Influence of DC Link Capacitance on Power Efficiency of Single-Phase Inverter

Physics-Informed Neural Networks (PINNs) have recently been proposed to solve scientific and engineering problems, where physical laws are introduced into neural networks as prior knowledge. With the embedded physical laws, PINNs enable the estimation of critical parameters, which are unobservable via physical tools, through observable variables. For example, Power Electronic Converters (PECs) are essential building blocks for the green energy transi-tion. PINNs have been applied to estimate the capacitance, which is unobservable during PEC operations, using current and voltage, which can be observed easily during operations. The estimated capacitance facilitates self-diagnostics of PECs. Existing PINNs are often manually designed, which is time-consuming and may lead to suboptimal performance due to a large number of design choices for neural network architectures and hyperparameters. In addition, PINNs are often deployed on different physical devices, e.g., PECs, with limited and varying resources. Therefore, it requires designing different PINN models under different resource constraints, making it an even more challenging task for manual design. To contend with the challenges, we propose Automated Physics-Informed Neural Networks (AutoPINN), a framework that enables the automated design of PINNs by combining AutoML and PINNs. Specifically, we first tailor a search space that allows finding high-accuracy PINNs for PEC internal parameter estimation. We then propose a resource-aware search strategy to explore the search space to find the best PINN model under different resource constraints. We experimentally demonstrate that AutoPINN is able to find more accurate PINN models than human-designed, state-of-the-art PINN models using fewer resources

AutoPINN: When AutoML Meets Physics-Informed Neural Networks

Condition monitoring (CM) methods applied for power electronics can provide effective information for predictive maintenance and prevent unexpected system downtime. This paper proposes a non-invasive and in-situ CM method for capacitors in modular multilevel converters. Unlike the conventional methods that monitor low-frequency signals, the proposed method focuses on high-frequency transient analysis. By analyzing the transient voltage at the capacitor’s charging moment with wavelet decomposition, the proposed method can estimate the capacitor’s equivalent series resistance in situ. Moreover, the proposed method based on high-frequency transients is decoupled from system operating states, while the conventional low-frequency signals are often affected by operations (e.g., loads, environments, etc.). Finally, the effectiveness of the proposed method has been validated in a 14kW case study by simulation.

Huai Wang

Papers

A reliability-oriented component sizing procedure for cost benchmarking of capacitive DC-links

A Dummy-Variable Model for Humidity-Influenced DC Film Capacitors Lifetime Estimation

Influence of DC Link Capacitance on Power Efficiency of Single-Phase Inverter

AutoPINN: When AutoML Meets Physics-Informed Neural Networks

Condition Monitoring for Capacitors in Modular Multilevel Converter based on High-frequency Transient Analysis